CN103684700B - 3D (three-dimensional) MU-MIMO (multiple user-multiple input multiple output) precoding method based on orthogonal joint codebook set - Google Patents
3D (three-dimensional) MU-MIMO (multiple user-multiple input multiple output) precoding method based on orthogonal joint codebook set Download PDFInfo
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Abstract
The invention discloses a 3D (three-dimensional) MU-MIMO (multiple user-multiple input multiple output) precoding method based on an orthogonal joint codebook set, and relates to the technical field of mobile communication. The method comprises the following steps of enabling a base station terminal to adopt a uniform surface antenna matrix, and simultaneously store the orthogonal joint codebook set together with a user terminal; according to a 3D MIMO channel matrix, enabling the user terminal to select the optimum precoding vector in the horizontal dimension and the vertical dimension; feeding the corresponding number of the precoding vector back to the base station terminal, enabling the base station terminal to form a 3D precoding matrix, and sending signals to a plurality of users to carry out the 3D precoding processing. The method has the advantages that the orthogonal joint codebook set covers larger space, and the orthogonality is formed between the codebooks, so the matching of the 3D MIMO channel is more accurate and comprehensive, and the interference of MU channel sharing is effectively inhibited; meanwhile, by selecting the optimum precoding matrix, under the condition of not increasing the feedback amount, the channel information in the horizontal dimension and the vertical dimension are comprehensively utilized, and the integral property of the system is improved.
Description
Technical field
The present invention relates to communication technical field, propose that one kind prelists mainly for LTE-Advanced system 3D MU-MIMO
Code method.
Background technology
As LTE-Advanced and LTE air interfaces core technology-MIMO technology, bandwidth and hair can not increased
In the case of penetrating power, power system capacity is improved, the mainly many antennas by being distributed in space are effectively combined time-domain
Received signal is processed with spatial domain, while using the multipath transmisstion characteristic and random fading characteristic of channel, effectively
Improve transmission quality and improve transmission rate.
However, in actual working environment, the embodiment of MIMO technology advantage depend heavilys on mimo channel model characteristics.
Therefore, setting up can effectively reflect that the channel model of true MIMO working environments just seems particularly significant.Existing MIMO letters
Road model is set up in two dimension mostly（2Dimension,2D）In plane.If simple from the point of view of Electromagnetic Wave Propagation mechanism, the channel
Model and imperfection, because the model only considers the horizontal transmission of spatial electromagnetic ripple, therefore 2D MIMO do not make full use of sky
Between resource.Therefore, academia has largely carried out the mimo channel modeling work based on 3D including industrial quarters.3D mimo channel moulds
Type requirement considers the horizontal and vertical propagation of spatial electromagnetic ripple simultaneously, that is, require to consider azimuth and the angle of pitch simultaneously, therefore, letter
Road model is more accurate.In view of the advantage of 3D MIMO technologies, industrial quarters includes the company such as high pass, A Lang, DOCOMO, Nuo Xi
Special advanced air interface (the Advanced Radio Interface Technologies for4G set up towards 4G
Systems, ARTIST4G) working group, the working group points out：3D MIMO technologies based on active array will be mobile as future
Communication system improves the key technology of cell edge user throughput and data transmission rate.At the same time, 3GPP was from year in 2012
Bottom starts to start the technical specification standard work of LTE-Advanced R12, formally using 3D MIMO technologies as LTE-
The core of Advanced R12 technical specifications.Taking this as an opportunity, has attracted domestic and international substantial amounts of scholar, engineer to be added to 3D
In MIMO key technologies and standardized research work.
In LTE-Advanced systems, the precoding technique based on 3D channels includes the selection of codebook design and code book
Deng.Common precoding codebook includes DFT（Discrete Fourier transform）Code book, random code book, Jim Glassman code book etc..For most
The selection of excellent precoding vectors is then based on different performance indications criterions.Such as, minimum singular value criterion, maximum capacity criterion
Deng.In pre-coding system based on code book, the code book that will have been designed first is stored in transmitting terminal and receiving terminal, receives termination
Signal is received, current CSI is obtained by channel estimation, then using CSI, in stored local code book, based on precoding
Criterion of Selecting selects optimal precoding vectors, and the call number corresponding to optimal precoding vectors is fed back into base station end, base station
Optimal precoding vectors are recovered in end by the call number, and generation pre-coding matrix carries out precoding processing to input data.
In 3D MIMO multi-user systems, with increasing for number of users, user distribution different zones in cell, including
Center of housing estate and cell edge.Traditional precoding technique with only the channel information of level dimension, and cannot tie up vertically
User is made a distinction, this has also resulted in serious inter-user interference.For example, the 3D precodings based on DFT code books, level dimension
Degree uses identical DFT code books with the code book of vertical dimensions, and level ties up optimal precoding vectors and the optimal precoding of vertical dimension
Vector is chosen by the DFT code books.Level dimension uses identical DFT code books with vertical Wiki in 3D pre-coding schemes, complete
Three dimensions characteristic is not accounted for entirely, so as to cause the rejection ability to CCI limited.Therefore, in order to lift center of housing estate simultaneously
With the capacity and user performance of Cell Edge User, demand combined level is tieed up and vertical dimension channel information, pre- to realize 3D MIMO
Coding.
The content of the invention
The present invention proposes a kind of 3D MU-MIMO method for precoding based on orthogonal joint codebook collection, comprising specific orthogonal
The construction method of joint codebook collection.Base station end uses uniform surface aerial array, and the orthogonal joint codebook is stored simultaneously with user terminal
Collection；User terminal carries out the selection of optimal precoding vectors in horizontal dimensions and vertical dimensions respectively, then will correspond to optimal prelisting
The call number of code vector feeds back to base station end；Base station end forms optimal precoding square according to the optimal precoding vectors of each user
Battle array, so as to carry out 3D precoding processings to multiuser transmission signal.
The present invention solve above-mentioned technical problem technical scheme be：A kind of 3D MU- based on orthogonal joint codebook collection of design
MIMO method for precoding, including step：Base station end uses surface antenna array structure, each antenna port to receive in two dimensional surface
Signal message and process signal message in three dimensions, construct orthogonal joint codebook collection and be stored in base station end and user simultaneously
End, user terminal channel is estimated to obtain 3D channel matrixes, according to 3D channel matrixes respectively in horizontal dimensions and vertical dimensions from just
Hand over joint codebook to concentrate the optimal precoding vectors of selection, and by the optimal precoding vectors in two dimensions in correspondence code book sequence
Number as feedback call number send back base station end, base station end recovers optimal precoding vectors according to the call number for receiving, give birth to
Precoding processing is carried out to input data into pre-coding matrix.
When according to DFT code books：Build basic code book Fbase
When：According to formula：It is determined that basic code book Fbase={T1,
T2,...,TLIn element Ti.The construction of orthogonal joint codebook collection includes：Level of coverage, code according to code book to channel space
This complexity and the pre-coding matrix selected by code book choose basic code book F to the rejection ability of CCIbase；By basic code book
FbaseOrthogonal transformation is carried out, mutually orthogonal orthogonal code book F' between each code word is obtainedbase；Extract basic code book Fbase={T1,
T2,...,TLIn any one code word Tl（l=1,2,...L）, according to formulaSeek
Look for corresponding L vectorOrthogonal sub-clustering code book is made up of L vectorThus
Obtain orthogonal sub-clustering code book collection Γ '={ Fbase_1,Fbase_2,...,Fbase_L, by the orthogonal sub-clustering code book collection Γ ' and basic code book
FbaseAccording to formula：Γ={{Fbase, Fbase_1},{Fbase, Fbase_2},...,{Fbase, Fbase_LCombine, obtain it is final just
Hand over joint codebook collection Γ.
Base station end generates pre-coding matrix specifically, base station end recovers all user's levels according to the call number for receiving
Optimal precoding vectors and the optimal precoding vectors of vertical dimension are tieed up, and 3D pre-coding matrixes are generated according to point multiplication operation.User terminal
Based on minimum singular value criterion is maximized, according to 3D channel matrixes, vertical dimensions are carried out respectively and is calculated with horizontal dimensions feedback quantity.
Client feeds back call number ties up optimal precoding vectors call number and the optimal precoding vectors call number of vertical dimension comprising level, its
In, level ties up the optimal precoding vectors of optimal precoding vectors call number correspondence most matching present level Vc SI in basic code
This FbaseSequence number, the optimal precoding vectors call number of vertical dimension is that level is tieed up corresponding to optimal precoding vectors call number just
Hand over sub-clustering code book Fbase_l。
Client feeds back to base station end optimal precoding vectors call number, not only comprising the optimal code vector that prelists of horizontal dimensions
Amount call number, while the optimal precoding vectors call number of vertical dimensions is contained, wherein, the optimal precoding vectors rope of horizontal dimensions
Quotation marks are certain precoding vectors of best match present level Vc SI in basic code book FbaseIn sequence number；Again by the level
Tie up optimal precoding vectors call number and determine corresponding orthogonal sub-clustering code book Fbase_lAs vertical dimension code book, so that vertically
Certain precoding vectors that optimal precoding vectors call number is best match current vertical dimension CSI are tieed up in the orthogonal sub-clustering code
This Fbase_lIn sequence number.
The design of orthogonal joint codebook collection not only combines horizontal dimensions with vertical dimensions CSI to carry out code book in the present invention
Design, and further contemplate level of coverage of the code book to 3D channels, and rejection ability of the 3D pre-coding matrixes for CCI.To sum up,
3D MU-MIMO method for precoding based on orthogonal joint codebook collection proposed by the present invention can obtain stronger pre-coding gain,
The overall performance of raising system.
Orthogonal joint codebook collection proposed by the invention not only covers bigger space, and exists between code book orthogonal
Property, therefore, the matching not only for 3D mimo channels is more accurate comprehensive, while multi-user's co-channel can also effectively be suppressed
Interference；In addition, the present invention can be under conditions of feedback quantity not be increased, level of comprehensive utilization is believed with the channel in vertical dimensions
Breath, improves the overall performance of system.
Brief description of the drawings
Fig. 1 is the system block diagram of 3D MU-MIMO method for precoding proposed by the present invention；
Fig. 2 is the pre-encode operation flow chart based on code book；
Fig. 3 is orthogonal sub-clustering codebook construction schematic diagram in the present invention；
Fig. 4 is orthogonal joint codebook collection organigram in the present invention；
Fig. 5 is 3D precodings concrete operations flow chart of the present invention；
Fig. 6 is " A1 " scene method for precoding of the present invention and DFT codebook precodings and fixed codebook under WINNER channels
Precoding bit error rate performance under identical feedback quantity compares figure；
Fig. 7 be method for precoding of the present invention with DFT codebook precodings and fixed codebook precoding under identical signal to noise ratio
CDF curve ratios relatively scheme；
Fig. 8 is Performance comparision figure of " A1 " the scene method for precoding under different codebook sizes under WINNER channels；
Specific embodiment
Below in conjunction with instantiation, present invention is described.
Fig. 1 is the 3D MU-MIMO method for precoding system block diagrams based on orthogonal joint codebook collection in the present invention.Base station end
Surface antenna array structure is tieed up using n × m, wherein n represents the line number of surface antenna array, and m represents the columns of surface antenna array, n=m.
It is required that each transmitting antenna can simultaneously process the information in horizontal dimensions and vertical dimensions.User terminal reception antenna number is used
R is represented.The signal that j-th user receives can be expressed as：
Signal is received to be made up of three parts, wherein, HjWjXjThe useful signal part that receiving terminal is received is represented,Represent the interference from other users signal that receives of j user, nj represents noise signal, for obedience CN (0,
N0) probability distribution white Gauss noise.User terminal obtains 3D channel matrix Hs by channel estimationn×m×r, choose accurate according to precoding
Then, respectively in horizontal dimensions and vertical dimensions, the optimal precoding vectors of selection are concentrated from orthogonal joint codebook, and by two dimensions
On optimal precoding vectors correspondence code book in sequence number feed back to base station end as call number, base station end is according to the rope for receiving
Quotation marks recover optimal precoding vectors, and then generation pre-coding matrix carries out precoding processing to input data.
Fig. 2 is the precoding basic operation flow chart based on code book, in LTE-Advanced systems, base station end and user
End stores code book simultaneously, and user terminal travels through all code words, the code word conduct that selection is matched with current CSI in the codebook according to CSI
Optimal precoding vectors, and by its in the codebook corresponding call number feed back to base station end, base station end is according to the index for receiving
Number recover optimal precoding vectors, and then form pre-coding matrix carries out precoding processing to input data.According to Fig. 5, and
With reference to Fig. 3 and Fig. 4, the realization of 3D MU-MIMO method for precoding is specifically included in the present invention：
Transmitting terminal uses surface antenna array structure, it is ensured that each transmitting antenna can simultaneously process horizontal dimensions and hang down
Information in straight dimension, user terminal uses r root reception antennas.The construction of orthogonal joint codebook collection, referring to shown in Fig. 3 and Fig. 4, has
Body is expressed as follows：
A, basic code book FbaseStructure
In view of discrete Fourier transform（Discrete Fourier Transformation, DFT）Code book has complexity
The characteristics of spending low, and precoding codebook specified in 3GPP standards is DFT code books, therefore selection DFT code books build basis
Code book, this example selects to illustrate implementation of the invention as a example by following DFT matrixes：
According to above formula, basic code book FbaseAs：
WhereinRepresent DFT matrixes in certain
One row, N is DFT code book numbers, code book number based on L, N=L.NtIt is antenna number, Nt=n.For other conventional code books, also may be used
Antenna number is combined according to the method described above builds basic code book.
B, orthogonal code book F'baseStructure
According to basic code book FbasE builds orthogonal code book F'base.To basic code book FbaseMiddle column vector { T1,T2,...,TL}
Do orthogonal transformation and obtain orthogonal code book F'base：
（Such as Fig. 3）；Due to orthogonal code book F'baseEach element
T'1,T'2,...,T'LBetween there is orthogonality, therefore by F'baseThe pre-coding matrix of composition equally will be with just
The property handed over, so as to be effectively guaranteed the suppression to CCI.
The composition of C, orthogonal joint codebook collection
In order to preferably utilize orthogonal code book in the 3 d space, it can in the lump be made transform expansion with basic code book, specifically
Operation is as shown in Figure 3.In the invention, basic code book is corresponding with CSI overall spaces, is done by any code word in basic code book
The dot product specified is converted, so as to obtain the sub-clustering of the orthogonal joint codebook corresponding with each basic code word, the sub-clustering and this
The corresponding CSI subspaces of basic code word are corresponding, and the present invention carries out orthogonal joint codebook design, and then by all sub-clustering collection structures
The joint codebook that is orthogonal collection.
Fig. 4 is a kind of detailed implementation process for constituting orthogonal sub-clustering code book for example, taking basic code book Fbase={T1,
T2,...,TLIn any one code word Tl（l=1,2,...L）, using relational expression
Find corresponding L vectorOrthogonal sub-clustering code book F is made up of this L vectorbase_l=[T1 l,T2 l,...,
TL l], such as in Fig. 3All code words in basic code book Fbase are equal
Make above-mentioned conversion, obtain associated orthogonal sub-clustering code book collection Γ a '={ Fbase_1,Fbase_2,...,Fbase_L, then by this just
Sub-clustering code book collection Γ ' is handed over basic code book FbaseAccording to formula Γ={ { Fbase, Fbase_1},{Fbase, Fbase_2},...,{Fbase,
Fbase_LBe combined, so as to obtain final orthogonal joint codebook collection Γ, wherein Γi={Fbase, Fbase_iRepresent the code book
The orthogonal joint codebook concentrated.
3D pre-coding scheme of the present invention based on orthogonal joint codebook collection, base station stores same one with user terminal jointly
The orthogonal joint codebook collection being made up of DFT matrixes, client feeds back call number ties up optimal precoding vectors call number comprising level
With the optimal precoding vectors call number of vertical dimension, wherein, level is tieed up a certain most matching of optimal precoding vectors call number correspondence and is worked as
The optimal precoding vectors of preceding horizontal Vc SI are in basic code book FbaseSequence number, the optimal precoding vectors call number of vertical dimension come
From the orthogonal sub-clustering code book F tieed up in level corresponding to optimal precoding vectors call numberbase_l, therefore, and based on DFT code books
3D precodings have same feedback quantity.Base station end recovers all user's levels and ties up optimal prelisting according to the call number for receiving
Code vector and the optimal precoding vectors of vertical dimension, and 3D pre-coding matrixes are generated according to point multiplication operation, it is ensured that 3D precoding squares
Each element has orthogonality in battle array, thus can well suppress CCI.In sum, the present invention in 3D pre-coding matrixes not
But current channel information space is more matched, while CCI can effectively be suppressed.
Orthogonal joint codebook collection is stored in base station end and user terminal simultaneously, user terminal is based on maximizing minimum singular value standard
Then, from basic code book FbaseThe middle optimal precoding vectors for determining matching present level dimensional channel information, from orthogonal joint code
This concentration selects to tie up the corresponding orthogonal sub-clustering code book F of optimal precoding vectors with the levelbase_l.As vertical dimensions code book,
Further according to maximization minimum singular value criterion from the orthogonal sub-clustering code book Fbase_lMiddle selection matching current vertical dimension letter the most
The optimal precoding vectors of road information.
Horizontal dimensions are maximization minimum singular value criterion with the optimal precoding vectors selection criterion of vertical dimensions：
Wherein WiRepresent code word in current code book, HWiRepresent equivalent channel, λmin{HxWyIt is HWiMinimum non-zero it is unusual
Value, ToptRepresent the optimal precoding vectors for traveling through and therefrom being selected after the code book.
By aforesaid operations, the optimal precoding vectors of horizontal dimensions that will be obtained are in basic code book FbaseMiddle correspondence sequence number is made
For level ties up optimal precoding vectors call number, meanwhile, the optimal precoding vectors of vertical dimension that will be obtained are in orthogonal sub-clustering code book
Fbase_lIn corresponding sequence number as the optimal precoding vectors call number of vertical dimension, finally, user terminal prelists level dimension is optimal
Code vector call number feeds back to base station end together with the optimal precoding vectors call number of vertical dimension.
In base station end, corresponding level dimension and the optimal code vector that prelists of vertical dimension are recovered according to the feedback call number for receiving
Amount, ties up optimal precoding vectors and constitutes level dimension pre-coding matrix W with the optimal precoding vectors of vertical dimension further according to levelhWith hang down
Straight dimension pre-coding matrix and Wv, by WhWith WvN and m is extended to respectively, then does the generation of dot product extended arithmetic and number of antennas
Corresponding pre-coding matrixW, W=[Wh;Wh;...Wh].×[Wv;Wv;...Wv], so, user is obtained using point multiplication operation
The W that W is obtained with other user using same procedureiBetween have very strong orthogonality such that it is able to suppress CCI well.
Sending and receiving end stores a same code book being made up of DFT matrixes.
Using " A1 " (Indoor office/residential) scene under WINNER, Fig. 6 gives for present invention emulation
3D method for precoding of the present invention and the 3D precodings based on DFT and the 3D method for precoding based on fixed codebook（Fixed codebook is only
Using two column vectors as code book）Bit error rate performance contrast under identical feedback quantity.It is 3 that Fig. 7 provides signal to noise ratio（dB）When,
Method for precoding of the present invention with based on DFT 3D precodings and the 3D method for precoding based on fixed codebook CDF curve ratios compared with.
It can be seen that the 3D pre-coding schemes based on orthogonal joint codebook collection proposed by the invention are relative to foregoing two kinds of precodings
Scheme has obvious advantage in BER performances and CDF curves.This is because the 3D method for precoding in the present invention is to current letter
The more accurate matching of road information realization, while having stronger CCI rejection abilities again.Fig. 8 show 3D of the present invention and prelists
Performance comparision of the code method under different codebook sizes, code book is bigger, and the channel information space for being covered is more accurate, but code book
Excessive, the feedback quantity of system will increase, and consider above-mentioned two aspect, select codebook size in a balanced way, and the present invention is according to letter
The factors such as road space, performance, feedback, codebook size optimal selection are 16.
Orthogonal joint codebook collection constructed by 3D MU-MIMO method for precoding proposed by the present invention is not only realized to 3D
The more accurate comprehensively covering of mimo channel, but also can effectively suppress multi-user's co-channel interference；Meanwhile, it is right in the present invention
In the selection of optimal pre-coding matrix, can take full advantage of level and believe with vertical dimensions under conditions of feedback quantity is not increased
Road information, therefore, the overall performance of system is obviously improved.
Claims (4)
1. a kind of 3D MU-MIMO method for precoding based on orthogonal joint codebook collection, it is characterised in that including step：Base station end
Using surface antenna array structure, each antenna port receives the signal message in two dimensional surface and processes signal in three dimensions
Information, constructs orthogonal joint codebook collection and is stored in base station end and user terminal simultaneously, and the construction of orthogonal joint codebook collection includes：Root
The pre-coding matrix selected to the level of coverage of channel space, code book complexity and by code book according to code book is to co-channel interference CCI
Rejection ability, choose basic code book Fbase, by basic code book FbaseOrthogonal transformation is carried out, obtains mutually orthogonal between each code word
Orthogonal code book F 'base, extract basic code book Fbase={ T1,T2,...,TLIn any one code word Tl, wherein, l=1,2 ...
L, according to formulaFind corresponding L vectorFrom L to
Amount constitutes orthogonal sub-clustering code bookIt is derived from orthogonal sub-clustering code book collection Γ '={ Fbase_1,
Fbase_2,...,Fbase_L, by the orthogonal sub-clustering code book collection Γ ' and basic code book FbaseAccording to formula：Γ={ { Fbase,
Fbase_1},{Fbase, Fbase_2},...,{Fbase, Fbase_LCombine, final orthogonal joint codebook collection Γ is obtained, wherein, T '1,
T′2,...,T′LIt is orthogonal code book F 'baseMiddle element；User terminal channel is estimated to obtain 3D channel matrixes, according to 3D channel matrixes
The optimal precoding vectors of selection are concentrated from orthogonal joint codebook with vertical dimensions in horizontal dimensions respectively, and by two dimensions
Sequence number of the optimal precoding vectors in correspondence code book feeds back to base station end as call number, and base station end is according to client feeds back
Call number recovers optimal precoding vectors, and generation 3D pre-coding matrixes carry out precoding processing to input data, and user terminal is anti-
The call number of feedback ties up optimal precoding vectors call number and the optimal precoding vectors call number of vertical dimension comprising level, wherein, water
The optimal precoding vectors of the flat optimal precoding vectors call number correspondence of dimension most matching present level dimension channel condition information CSI exist
Basic code book FbaseSequence number, to tie up optimal precoding vectors call number right for level for the optimal precoding vectors call number of vertical dimension
The orthogonal sub-clustering code book F for answeringbase_l。
2. method according to claim 1, it is characterised in that base station end generates 3D pre-coding matrixes specifically, base station end
Call number according to receiving recovers all user's levels and ties up optimal precoding vectors and the optimal precoding vectors of vertical dimension, and
3D pre-coding matrixes are generated according to point multiplication operation.
3. method according to claim 1 and 2, it is characterised in that user terminal is based on maximizing minimum singular value criterion, root
According to 3D channel matrixes, vertical dimensions are carried out respectively and is calculated with horizontal dimensions feedback quantity.
4. method according to claim 1 and 2, it is characterised in that when according to discrete Fourier transform DFT code books：
Build basic code book FbaseWhen：According to formula：I=1,2 ..., L；It is determined that basic code book Fbase={ T1,T2,...,
TLIn element Ti。
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| CN105024780B (en) * | 2014-04-23 | 2018-08-10 | 中国移动通信集团公司 | A kind of information sends, determines and channel reconstruction method and relevant apparatus and system |
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| CN104184555B (en) * | 2014-09-03 | 2017-06-23 | 西安电子科技大学 | A kind of method for precoding based on dicode sheet suitable for 3D mimo systems |
| CN104184690B (en) * | 2014-09-03 | 2017-04-12 | 西安电子科技大学 | Double-layer pre-coding method applicable to 3D MIMO system |
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| CN106452536B (en) * | 2015-08-07 | 2019-09-06 | 上海诺基亚贝尔股份有限公司 | The method and apparatus of long-term feedback for multiple input multiple output communications |
| CN105703814B (en) * | 2016-03-24 | 2018-12-28 | 河北工业大学 | A kind of choosing method of the rotation DFT code book for 3D MIMO |
| CN105721029B (en) * | 2016-04-27 | 2019-02-05 | 西安交通大学 | Multi-user dispatching method based on this Limited Feedback of dicode in 3D MU-MIMO FDD system |
| CN108282203B (en) * | 2017-01-05 | 2021-08-10 | 中国移动通信集团四川有限公司 | Method and apparatus for wireless communication |
| CN107332597B (en) * | 2017-06-05 | 2021-05-28 | 惠州Tcl移动通信有限公司 | Wireless transmission method and device based on 3D MIMO |
| CN108199808B (en) * | 2018-02-11 | 2023-09-01 | 浙江大学 | Method for improving information transmission efficiency |
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| CN111555784B (en) * | 2020-05-19 | 2021-10-22 | 北京邮电大学 | Precoding method and device and electronic equipment |
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